The present invention relates to a method of analyzing an object data set comprising points in a multi-dimensional space, in which data set a tubular structure occurs which is represented on a display screen, said method comprising the following steps:    a) choosing a screen position related to the tubular structure;    b) determining the multi-dimensional co-ordinates of a starting position associated with said screen position;    c) deriving a plane through said starting position having its normal directed to the tubular structure;    d) determining a surface point of the tubular structure as a target position associated with the starting position.
The invention also relates to a computer program to carry out a method of analyzing an object data set comprising points in a multi-dimensional space, in which data set a tubular structure occurs.
The international patent application EP00/09505 of the same applicant relates to a method of the type mentioned above. The method described in the above cited patent application relates in general to the analysis of a tubular structure in a multi-dimensional space. According to this method a self-adjusting probe is defined for analysis of the object data set. The self-adjusting probe comprises a sphere and a plane through the center of the sphere. The sphere should be positioned such that the tubular structure intersects the sphere, that is, at least partially. The plane should be oriented orthogonally to the tubular structure. When oriented correctly the self-adjusting probe enables semiautomatic shape extraction of a tube-like geometry.
Such an object data set represents one or more properties of the object to be examined. The object data set notably relates to the density distribution in the object to be examined; in that case the data values are the local density values of (a part of) the object to be examined. The data values may alternatively relate, for example, to the distribution of the temperature or the magnetization in the object. The multi-dimensional space is usually a three-dimensional space. The data values then relate to a volume distribution of the relevant property, for example, the density distribution in a volume of the object to be examined. The multi-dimensional space may alternatively be two-dimensional. In that case the data values relate to a distribution of the relevant property in a plane through the object, for example, the density distribution in a cross-section through the object.
The object data set can be acquired in a variety of ways. The object data set notably relates to a patient to be examined. Such an object data set can be acquired by means of various techniques such as, for example, 3D X-ray rotational angiography, computed tomography, magnetic resonance imaging or magnetic resonance angiography.
The known method is particularly suitable for analyzing the structure of blood vessels. Several physical characteristics of a blood vessel, such as the diameter thereof, can be determined. Accurate determination of these physical characteristics might be crucial for accurate diagnosis and safe treatment of, for example, a stenosis or an aneurysm.
Currently, at the start of an analysis the user chooses a starting point related to the tubular structure. This is done interactively by means of a pointing device, i.e. by selecting a point on a display screen showing the tubular structure in three views. To obtain an accurate determination of the physical characteristics it is desirable that this starting point is selected accurately and in a reproducible manner.